{"id":"W3105475479","doi":"10.1002/adfm.202007598","title":"Polymer‐Based Solid Electrolytes: Material Selection, Design, and Application","year":2020,"lang":"en","type":"article","venue":"Advanced Functional Materials","topic":"Advanced Battery Materials and Technologies","field":"Engineering","cited_by":402,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"Fundamental Research Funds for the Central Universities; National Key Research and Development Program of China; Natural Sciences and Engineering Research Council of Canada; Natural Science Foundation of Guangdong Province; National Natural Science Foundation of China","keywords":"Flexibility (engineering); Materials science; Lithium (medication); Polymer electrolytes; Electrolyte; Fast ion conductor; Polymer; Solid-state; Energy density; Nanotechnology; Computer science; Process engineering; Ionic conductivity; Engineering physics; Engineering; Composite material; Electrode; Chemistry","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0000672138,0.0002445991,0.0002791162,0.00005900043,0.0001123937,0.00007505428,0.00009150789,0.0001136056,0.0003191363],"category_scores_gemma":[0.0000290668,0.0002430085,0.00002171062,0.0001517645,0.00005269832,0.0002697905,0.00002874704,0.0000661283,0.00005308188],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003782275,"about_ca_system_score_gemma":0.00001578521,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001695044,"about_ca_topic_score_gemma":2.822842e-7,"domain_scores_codex":[0.9989403,0.00002908553,0.0003141437,0.0003128806,0.0001218315,0.0002817005],"domain_scores_gemma":[0.999649,0.00004615955,0.00006946052,0.0001170505,0.00004580196,0.00007247012],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0002413155,0.000008467123,0.000008655937,0.0000651935,0.00002044166,9.087447e-7,0.000006955851,0.03583142,0.961041,0.0004498622,0.0003106844,0.002015115],"study_design_scores_gemma":[0.0004233209,0.0001458177,0.000189439,0.00001024231,0.00001542982,0.000009137204,0.000007499514,0.005122871,0.9913744,0.0009731823,0.001470902,0.0002577198],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3967866,0.0001355869,0.5998226,0.0004681511,0.0005806449,0.0004140303,0.00007327966,0.001687172,0.00003194766],"genre_scores_gemma":[0.9899637,0.0000578263,0.008791507,0.0004103082,0.0003302801,0.0002839635,0.00009343597,0.0000582631,0.00001074977],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.5931771,"threshold_uncertainty_score":0.9909599,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009429400777710479,"score_gpt":0.2030841568246918,"score_spread":0.1936547560469813,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}